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// Copyright (C) 2019-2021 Garth N. Wells and Jørgen S. Dokken
//
// This file is part of DOLFINx (https://www.fenicsproject.org)
//
// SPDX-License-Identifier: LGPL-3.0-or-later
#pragma once
#include "BoundingBoxTree.h"
#include "gjk.h"
#include <algorithm>
#include <array>
#include <concepts>
#include <cstdint>
#include <deque>
#include <dolfinx/graph/AdjacencyList.h>
#include <dolfinx/mesh/Mesh.h>
#include <map>
#include <numeric>
#include <span>
#include <vector>
namespace dolfinx::geometry
{
/// @brief Information on the ownership of points distributed across
/// processes.
/// @tparam T Mesh geometry floating type.
template <std::floating_point T>
struct PointOwnershipData
{
std::vector<int> src_owner; ///< Ranks owning each point sent into ownership
///< determination for current process
std::vector<int>
dest_owners; ///< Ranks that sent `dest_points` to current process
std::vector<T> dest_points; ///< Points that are owned by current process
std::vector<std::int32_t>
dest_cells; ///< Cell indices (local to process) where each entry of
///< `dest_points` is located
};
/// @brief Compute the shortest vector from a mesh entity to a point.
///
/// @param[in] mesh The mesh
/// @param[in] dim Topological dimension of the mesh entity
/// @param[in] entities List of entities
/// @param[in] points Set of points (`shape=(num_points, 3)`), using
/// row-major storage.
/// @return An array of vectors (shape=(num_points, 3)) where the ith
/// row is the shortest vector between the ith entity and the ith point.
/// Storage is row-major.
template <std::floating_point T>
std::vector<T> shortest_vector(const mesh::Mesh<T>& mesh, int dim,
std::span<const std::int32_t> entities,
std::span<const T> points)
{
const int tdim = mesh.topology()->dim();
const mesh::Geometry<T>& geometry = mesh.geometry();
std::span<const T> geom_dofs = geometry.x();
auto x_dofmap = geometry.dofmap();
std::vector<T> shortest_vectors;
shortest_vectors.reserve(3 * entities.size());
if (dim == tdim)
{
for (std::size_t e = 0; e < entities.size(); e++)
{
// Check that we have sent in valid entities, i.e. that they exist in the
// local dofmap. One gets a cryptical memory segfault if entities is -1
assert(entities[e] >= 0);
auto dofs = MDSPAN_IMPL_STANDARD_NAMESPACE::submdspan(
x_dofmap, entities[e], MDSPAN_IMPL_STANDARD_NAMESPACE::full_extent);
std::vector<T> nodes(3 * dofs.size());
for (std::size_t i = 0; i < dofs.size(); ++i)
{
const std::int32_t pos = 3 * dofs[i];
for (std::size_t j = 0; j < 3; ++j)
nodes[3 * i + j] = geom_dofs[pos + j];
}
std::array<T, 3> d
= compute_distance_gjk<T>(points.subspan(3 * e, 3), nodes);
shortest_vectors.insert(shortest_vectors.end(), d.begin(), d.end());
}
}
else
{
mesh.topology_mutable()->create_connectivity(dim, tdim);
mesh.topology_mutable()->create_connectivity(tdim, dim);
auto e_to_c = mesh.topology()->connectivity(dim, tdim);
assert(e_to_c);
auto c_to_e = mesh.topology_mutable()->connectivity(tdim, dim);
assert(c_to_e);
for (std::size_t e = 0; e < entities.size(); e++)
{
const std::int32_t index = entities[e];
// Find attached cell
assert(e_to_c->num_links(index) > 0);
const std::int32_t c = e_to_c->links(index)[0];
// Find local number of entity wrt cell
auto cell_entities = c_to_e->links(c);
auto it0 = std::find(cell_entities.begin(), cell_entities.end(), index);
assert(it0 != cell_entities.end());
const int local_cell_entity = std::distance(cell_entities.begin(), it0);
// Tabulate geometry dofs for the entity
auto dofs = MDSPAN_IMPL_STANDARD_NAMESPACE::submdspan(
x_dofmap, c, MDSPAN_IMPL_STANDARD_NAMESPACE::full_extent);
const std::vector<int> entity_dofs
= geometry.cmap().create_dof_layout().entity_closure_dofs(
dim, local_cell_entity);
std::vector<T> nodes(3 * entity_dofs.size());
for (std::size_t i = 0; i < entity_dofs.size(); i++)
{
const std::int32_t pos = 3 * dofs[entity_dofs[i]];
for (std::size_t j = 0; j < 3; ++j)
nodes[3 * i + j] = geom_dofs[pos + j];
}
std::array<T, 3> d
= compute_distance_gjk<T>(points.subspan(3 * e, 3), nodes);
shortest_vectors.insert(shortest_vectors.end(), d.begin(), d.end());
}
}
return shortest_vectors;
}
/// @brief Compute squared distance between point and bounding box.
///
/// @param[in] b Bounding box coordinates
/// @param[in] x A point
/// @return The shortest distance between the bounding box `b` and the
/// point `x`. Returns zero if `x` is inside box.
template <std::floating_point T>
T compute_squared_distance_bbox(std::span<const T, 6> b,
std::span<const T, 3> x)
{
auto b0 = b.template subspan<0, 3>();
auto b1 = b.template subspan<3, 3>();
return std::transform_reduce(x.begin(), x.end(), b0.begin(), 0.0,
std::plus<>{},
[](auto x, auto b)
{
auto dx = x - b;
return dx > 0 ? 0 : dx * dx;
})
+ std::transform_reduce(x.begin(), x.end(), b1.begin(), 0.0,
std::plus<>{},
[](auto x, auto b)
{
auto dx = x - b;
return dx < 0 ? 0 : dx * dx;
});
}
/// @brief Compute the squared distance between a point and a mesh
/// entity.
///
/// The distance is computed between the ith input points and the ith
/// input entity.
///
/// @note Uses the GJK algorithm, see geometry::compute_distance_gjk for
/// details.
/// @note Uses a convex hull approximation of linearized geometry
/// @param[in] mesh Mesh containing the entities
/// @param[in] dim The topological dimension of the mesh entities
/// @param[in] entities The indices of the mesh entities (local to process)
/// @param[in] points The set points from which to computed the shortest
/// (shape=(num_points, 3)). Storage is row-major.
/// @return Squared shortest distance from points[i] to entities[i]
template <std::floating_point T>
std::vector<T> squared_distance(const mesh::Mesh<T>& mesh, int dim,
std::span<const std::int32_t> entities,
std::span<const T> points)
{
std::vector<T> v = shortest_vector(mesh, dim, entities, points);
std::vector<T> d(v.size() / 3, 0);
for (std::size_t i = 0; i < d.size(); ++i)
for (std::size_t j = 0; j < 3; ++j)
d[i] += v[3 * i + j] * v[3 * i + j];
return d;
}
namespace impl
{
/// Check whether bounding box is a leaf node
constexpr bool is_leaf(std::array<int, 2> bbox)
{
// Leaf nodes are marked by setting child_0 equal to child_1
return bbox[0] == bbox[1];
}
/// A point `x` is inside a bounding box `b` if each component of its
/// coordinates lies within the range `[b(0,i), b(1,i)]` that defines
/// the bounds of the bounding box, b(0,i) <= x[i] <= b(1,i) for i = 0,
/// 1, 2
template <std::floating_point T>
constexpr bool point_in_bbox(const std::array<T, 6>& b, std::span<const T, 3> x)
{
constexpr T rtol = 1e-14;
bool in = true;
for (std::size_t i = 0; i < 3; i++)
{
T eps = rtol * (b[i + 3] - b[i]);
in &= x[i] >= (b[i] - eps);
in &= x[i] <= (b[i + 3] + eps);
}
return in;
}
/// A bounding box "a" is contained inside another bounding box "b", if
/// each of its intervals [a(0,i), a(1,i)] is contained in [b(0,i),
/// b(1,i)], a(0,i) <= b(1, i) and a(1,i) >= b(0, i)
template <std::floating_point T>
constexpr bool bbox_in_bbox(std::span<const T, 6> a, std::span<const T, 6> b)
{
constexpr T rtol = 1e-14;
auto a0 = a.template subspan<0, 3>();
auto a1 = a.template subspan<3, 3>();
auto b0 = b.template subspan<0, 3>();
auto b1 = b.template subspan<3, 3>();
bool in = true;
for (std::size_t i = 0; i < 3; i++)
{
T eps = rtol * (b1[i] - b0[i]);
in &= a1[i] >= (b0[i] - eps);
in &= a0[i] <= (b1[i] + eps);
}
return in;
}
/// Compute closest entity {closest_entity, R2} (recursive)
template <std::floating_point T>
std::pair<std::int32_t, T>
_compute_closest_entity(const geometry::BoundingBoxTree<T>& tree,
std::span<const T, 3> point, std::int32_t node,
const mesh::Mesh<T>& mesh, std::int32_t closest_entity,
T R2)
{
// Get children of current bounding box node (child_1 denotes entity
// index for leaves)
const std::array<int, 2> bbox = tree.bbox(node);
T r2;
if (is_leaf(bbox))
{
// If point cloud tree the exact distance is easy to compute
if (tree.tdim() == 0)
{
std::array<T, 6> diff = tree.get_bbox(node);
for (std::size_t k = 0; k < 3; ++k)
diff[k] -= point[k];
r2 = diff[0] * diff[0] + diff[1] * diff[1] + diff[2] * diff[2];
}
else
{
r2 = compute_squared_distance_bbox<T>(tree.get_bbox(node), point);
// If bounding box closer than previous closest entity, use gjk to
// obtain exact distance to the convex hull of the entity
if (r2 <= R2)
{
r2 = squared_distance<T>(mesh, tree.tdim(),
std::span(std::next(bbox.begin(), 1), 1),
point)
.front();
}
}
// If entity is closer than best result so far, return it
if (r2 <= R2)
{
closest_entity = bbox.back();
R2 = r2;
}
return {closest_entity, R2};
}
else
{
// If bounding box is outside radius, then don't search further
r2 = compute_squared_distance_bbox<T>(tree.get_bbox(node), point);
if (r2 > R2)
return {closest_entity, R2};
// Check both children
// We use R2 (as opposed to r2), as a bounding box can be closer
// than the actual entity
std::pair<int, T> p0 = _compute_closest_entity(tree, point, bbox.front(),
mesh, closest_entity, R2);
std::pair<int, T> p1 = _compute_closest_entity(tree, point, bbox.back(),
mesh, p0.first, p0.second);
return p1;
}
}
/// @brief Compute collisions with a single point.
/// @param[in] tree The bounding box tree
/// @param[in] points The points (`shape=(num_points, 3)`)
/// @param[in, out] entities The list of colliding entities (local to
/// process)
template <std::floating_point T>
void _compute_collisions_point(const geometry::BoundingBoxTree<T>& tree,
std::span<const T, 3> p,
std::vector<std::int32_t>& entities)
{
std::deque<std::int32_t> stack;
std::int32_t next = tree.num_bboxes() - 1;
while (next != -1)
{
const std::array<int, 2> bbox = tree.bbox(next);
if (is_leaf(bbox) and point_in_bbox(tree.get_bbox(next), p))
{
// If box is a leaf node then add it to the list of colliding
// entities
entities.push_back(bbox[1]);
next = -1;
}
else
{
// Check whether the point collides with child nodes (left and
// right)
bool left = point_in_bbox(tree.get_bbox(bbox[0]), p);
bool right = point_in_bbox(tree.get_bbox(bbox[1]), p);
if (left and right)
{
// If the point collides with both child nodes, add the right
// node to the stack (for later visiting) and continue the tree
// traversal with the left subtree
stack.push_back(bbox[1]);
next = bbox[0];
}
else if (left)
{
// Traverse the current node's left subtree
next = bbox[0];
}
else if (right)
{
// Traverse the current node's right subtree
next = bbox[1];
}
else
next = -1;
}
// If tree traversal reaches a dead end (box is a leaf node or no
// collision detected), check the stack for deferred subtrees
if (next == -1 and !stack.empty())
{
next = stack.back();
stack.pop_back();
}
}
}
// Compute collisions with tree (recursive)
template <std::floating_point T>
void _compute_collisions_tree(const geometry::BoundingBoxTree<T>& A,
const geometry::BoundingBoxTree<T>& B,
std::int32_t node_A, std::int32_t node_B,
std::vector<std::int32_t>& entities)
{
// If bounding boxes don't collide, then don't search further
if (!bbox_in_bbox<T>(A.get_bbox(node_A), B.get_bbox(node_B)))
return;
// Get bounding boxes for current nodes
const std::array<std::int32_t, 2> bbox_A = A.bbox(node_A);
const std::array<std::int32_t, 2> bbox_B = B.bbox(node_B);
// Check whether we've reached a leaf in A or B
const bool is_leaf_A = is_leaf(bbox_A);
const bool is_leaf_B = is_leaf(bbox_B);
if (is_leaf_A and is_leaf_B)
{
// If both boxes are leaves (which we know collide), then add them
// child_1 denotes entity for leaves
entities.push_back(bbox_A[1]);
entities.push_back(bbox_B[1]);
}
else if (is_leaf_A)
{
// If we reached the leaf in A, then descend B
_compute_collisions_tree(A, B, node_A, bbox_B[0], entities);
_compute_collisions_tree(A, B, node_A, bbox_B[1], entities);
}
else if (is_leaf_B)
{
// If we reached the leaf in B, then descend A
_compute_collisions_tree(A, B, bbox_A[0], node_B, entities);
_compute_collisions_tree(A, B, bbox_A[1], node_B, entities);
}
else if (node_A > node_B)
{
// At this point, we know neither is a leaf so descend the largest
// tree first. Note that nodes are added in reverse order with the
// top bounding box at the end so the largest tree (the one with the
// the most boxes left to traverse) has the largest node number.
_compute_collisions_tree(A, B, bbox_A[0], node_B, entities);
_compute_collisions_tree(A, B, bbox_A[1], node_B, entities);
}
else
{
_compute_collisions_tree(A, B, node_A, bbox_B[0], entities);
_compute_collisions_tree(A, B, node_A, bbox_B[1], entities);
}
// Note that cases above can be collected in fewer cases but this way
// the logic is easier to follow.
}
} // namespace impl
/// @brief Create a bounding box tree for the midpoints of a subset of
/// entities.
/// @param[in] mesh The mesh
/// @param[in] tdim The topological dimension of the entity
/// @param[in] entities List of local entity indices
/// @return Bounding box tree for midpoints of entities
template <std::floating_point T>
BoundingBoxTree<T> create_midpoint_tree(const mesh::Mesh<T>& mesh, int tdim,
std::span<const std::int32_t> entities)
{
spdlog::info("Building point search tree to accelerate distance queries for "
"a given topological dimension and subset of entities.");
const std::vector<T> midpoints
= mesh::compute_midpoints(mesh, tdim, entities);
std::vector<std::pair<std::array<T, 3>, std::int32_t>> points(
entities.size());
for (std::size_t i = 0; i < points.size(); ++i)
{
for (std::size_t j = 0; j < 3; ++j)
points[i].first[j] = midpoints[3 * i + j];
points[i].second = entities[i];
}
// Build tree
return BoundingBoxTree(points);
}
/// @brief Compute all collisions between two bounding box trees.
/// @param[in] tree0 First BoundingBoxTree
/// @param[in] tree1 Second BoundingBoxTree
/// @return List of pairs of intersecting box indices from each tree,
/// flattened as a vector of size num_intersections*2
template <std::floating_point T>
std::vector<std::int32_t> compute_collisions(const BoundingBoxTree<T>& tree0,
const BoundingBoxTree<T>& tree1)
{
// Call recursive find function
std::vector<std::int32_t> entities;
if (tree0.num_bboxes() > 0 and tree1.num_bboxes() > 0)
{
impl::_compute_collisions_tree(tree0, tree1, tree0.num_bboxes() - 1,
tree1.num_bboxes() - 1, entities);
}
return entities;
}
/// @brief Compute collisions between points and leaf bounding boxes.
///
/// Bounding boxes can overlap, therefore points can collide with more
/// than one box.
///
/// @param[in] tree The bounding box tree
/// @param[in] points The points (`shape=(num_points, 3)`). Storage is
/// row-major.
/// @return For each point, the bounding box leaves that collide with
/// the point.
template <std::floating_point T>
graph::AdjacencyList<std::int32_t>
compute_collisions(const BoundingBoxTree<T>& tree, std::span<const T> points)
{
if (tree.num_bboxes() > 0)
{
std::vector<std::int32_t> entities, offsets(points.size() / 3 + 1, 0);
entities.reserve(points.size() / 3);
for (std::size_t p = 0; p < points.size() / 3; ++p)
{
impl::_compute_collisions_point(
tree, std::span<const T, 3>(points.data() + 3 * p, 3), entities);
offsets[p + 1] = entities.size();
}
return graph::AdjacencyList(std::move(entities), std::move(offsets));
}
else
{
return graph::AdjacencyList(
std::vector<std::int32_t>(),
std::vector<std::int32_t>(points.size() / 3 + 1, 0));
}
}
/// @brief Given a set of cells, find the first one that collides with a
/// point.
///
/// A point can collide with more than one cell. The first cell detected
/// to collide with the point is returned. If no collision is detected,
/// -1 is returned.
///
/// @note `cells` can for instance be found by using
/// geometry::compute_collisions between a bounding box tree for the
/// cells of the mesh and the point.
///
/// @param[in] mesh The mesh.
/// @param[in] cells Candidate cells.
/// @param[in] point The point (`shape=(3,)`).
/// @param[in] tol Tolerance for accepting a collision (in the squared
/// distance).
/// @return Local cell index, -1 if not found.
template <std::floating_point T>
std::int32_t compute_first_colliding_cell(const mesh::Mesh<T>& mesh,
std::span<const std::int32_t> cells,
std::array<T, 3> point, T tol)
{
if (cells.empty())
return -1;
else
{
const mesh::Geometry<T>& geometry = mesh.geometry();
std::span<const T> geom_dofs = geometry.x();
auto x_dofmap = geometry.dofmap();
const std::size_t num_nodes = x_dofmap.extent(1);
std::vector<T> coordinate_dofs(num_nodes * 3);
for (auto cell : cells)
{
auto dofs = MDSPAN_IMPL_STANDARD_NAMESPACE::submdspan(
x_dofmap, cell, MDSPAN_IMPL_STANDARD_NAMESPACE::full_extent);
for (std::size_t i = 0; i < num_nodes; ++i)
{
std::copy_n(std::next(geom_dofs.begin(), 3 * dofs[i]), 3,
std::next(coordinate_dofs.begin(), 3 * i));
}
std::array<T, 3> shortest_vector
= compute_distance_gjk<T>(point, coordinate_dofs);
T d2 = std::reduce(shortest_vector.begin(), shortest_vector.end(), T(0),
[](auto d, auto e) { return d + e * e; });
if (d2 < tol)
return cell;
}
return -1;
}
}
/// @brief Compute closest mesh entity to a point.
///
/// @note Returns a vector filled with index -1 if the bounding box tree
/// is empty.
///
/// @param[in] tree The bounding box tree for the entities
/// @param[in] midpoint_tree A bounding box tree with the midpoints of
/// all the mesh entities. This is used to accelerate the search.
/// @param[in] mesh The mesh
/// @param[in] points The set of points (`shape=(num_points, 3)`).
/// Storage is row-major.
/// @return For each point, the index of the closest mesh entity.
template <std::floating_point T>
std::vector<std::int32_t>
compute_closest_entity(const BoundingBoxTree<T>& tree,
const BoundingBoxTree<T>& midpoint_tree,
const mesh::Mesh<T>& mesh, std::span<const T> points)
{
if (tree.num_bboxes() == 0)
return std::vector<std::int32_t>(points.size() / 3, -1);
std::vector<std::int32_t> entities;
entities.reserve(points.size() / 3);
for (std::size_t i = 0; i < points.size() / 3; ++i)
{
// Use midpoint tree to find initial closest entity to the point.
// Start by using a leaf node as the initial guess for the input
// entity
std::array<int, 2> leaf0 = midpoint_tree.bbox(0);
assert(impl::is_leaf(leaf0));
std::array<T, 6> diff = midpoint_tree.get_bbox(0);
for (std::size_t k = 0; k < 3; ++k)
diff[k] -= points[3 * i + k];
T R2 = diff[0] * diff[0] + diff[1] * diff[1] + diff[2] * diff[2];
// Use a recursive search through the bounding box tree
// to find determine the entity with the closest midpoint.
// As the midpoint tree only consist of points, the distance
// queries are lightweight.
const auto [m_index, m_distance2] = impl::_compute_closest_entity(
midpoint_tree, std::span<const T, 3>(points.data() + 3 * i, 3),
midpoint_tree.num_bboxes() - 1, mesh, leaf0[0], R2);
// Use a recursives search through the bounding box tree to
// determine which entity is actually closest.
// Uses the entity with the closest midpoint as initial guess, and
// the distance from the midpoint to the point of interest as the
// initial search radius.
const auto [index, distance2] = impl::_compute_closest_entity(
tree, std::span<const T, 3>(points.data() + 3 * i, 3),
tree.num_bboxes() - 1, mesh, m_index, m_distance2);
entities.push_back(index);
}
return entities;
}
/// @brief Compute which cells collide with a point.
///
/// @note Uses the GJK algorithm, see geometry::compute_distance_gjk for
/// details.
///
/// @note `candidate_cells` can for instance be found by using
/// geometry::compute_collisions between a bounding box tree and the set
/// of points.
///
/// @param[in] mesh The mesh
/// @param[in] candidate_cells List of candidate colliding cells for the
/// ith point in `points`
/// @param[in] points Points to check for collision (`shape=(num_points,
/// 3)`). Storage is row-major.
/// @return For each point, the cells that collide with the point.
template <std::floating_point T>
graph::AdjacencyList<std::int32_t> compute_colliding_cells(
const mesh::Mesh<T>& mesh,
const graph::AdjacencyList<std::int32_t>& candidate_cells,
std::span<const T> points)
{
std::vector<std::int32_t> offsets = {0};
offsets.reserve(candidate_cells.num_nodes() + 1);
std::vector<std::int32_t> colliding_cells;
constexpr T eps2 = 1e-12;
const int tdim = mesh.topology()->dim();
for (std::int32_t i = 0; i < candidate_cells.num_nodes(); i++)
{
auto cells = candidate_cells.links(i);
std::vector<T> _point(3 * cells.size());
for (std::size_t j = 0; j < cells.size(); ++j)
for (std::size_t k = 0; k < 3; ++k)
_point[3 * j + k] = points[3 * i + k];
std::vector distances_sq = squared_distance<T>(mesh, tdim, cells, _point);
for (std::size_t j = 0; j < cells.size(); j++)
if (distances_sq[j] < eps2)
colliding_cells.push_back(cells[j]);
offsets.push_back(colliding_cells.size());
}
return graph::AdjacencyList(std::move(colliding_cells), std::move(offsets));
}
/// @brief Given a set of points, determine which process is colliding,
/// using the GJK algorithm on cells to determine collisions.
///
/// @todo This docstring is unclear. Needs fixing.
///
/// @param[in] mesh The mesh
/// @param[in] points Points to check for collision (`shape=(num_points,
/// 3)`). Storage is row-major.
/// @param[in] padding Amount of absolute padding of bounding boxes of the mesh.
/// Each bounding box of the mesh is padded with this amount, to increase
/// the number of candidates, avoiding rounding errors in determining the owner
/// of a point if the point is on the surface of a cell in the mesh.
/// @return Tuple `(src_owner, dest_owner, dest_points, dest_cells)`,
/// where src_owner is a list of ranks corresponding to the input
/// points. dest_owner is a list of ranks corresponding to dest_points,
/// the points that this process owns. dest_cells contains the
/// corresponding cell for each entry in dest_points.
///
/// @note `dest_owner` is sorted
/// @note Returns -1 if no colliding process is found
/// @note dest_points is flattened row-major, shape `(dest_owner.size(),
/// 3)`
/// @note Only looks through cells owned by the process
/// @note A large padding value can increase the runtime of the function by
/// orders of magnitude, because for non-colliding cells
/// one has to determine the closest cell among all processes with an
/// intersecting bounding box, which is an expensive operation to perform.
template <std::floating_point T>
PointOwnershipData<T> determine_point_ownership(const mesh::Mesh<T>& mesh,
std::span<const T> points,
T padding)
{
MPI_Comm comm = mesh.comm();
// Create a global bounding-box tree to find candidate processes with
// cells that could collide with the points
const int tdim = mesh.topology()->dim();
auto cell_map = mesh.topology()->index_map(tdim);
const std::int32_t num_cells = cell_map->size_local();
// NOTE: Should we send the cells in as input?
std::vector<std::int32_t> cells(num_cells, 0);
std::iota(cells.begin(), cells.end(), 0);
BoundingBoxTree bb(mesh, tdim, cells, padding);
BoundingBoxTree global_bbtree = bb.create_global_tree(comm);
// Compute collisions:
// For each point in `points` get the processes it should be sent to
graph::AdjacencyList collisions = compute_collisions(global_bbtree, points);
// Get unique list of outgoing ranks
std::vector<std::int32_t> out_ranks = collisions.array();
std::ranges::sort(out_ranks);
auto [unique_end, range_end] = std::ranges::unique(out_ranks);
out_ranks.erase(unique_end, range_end);
// Compute incoming edges (source processes)
std::vector in_ranks = dolfinx::MPI::compute_graph_edges_nbx(comm, out_ranks);
std::ranges::sort(in_ranks);
// Create neighborhood communicator in forward direction
MPI_Comm forward_comm;
MPI_Dist_graph_create_adjacent(
comm, in_ranks.size(), in_ranks.data(), MPI_UNWEIGHTED, out_ranks.size(),
out_ranks.data(), MPI_UNWEIGHTED, MPI_INFO_NULL, false, &forward_comm);
// Compute map from global mpi rank to neighbor rank, "collisions"
// uses global rank
std::map<std::int32_t, std::int32_t> rank_to_neighbor;
for (std::size_t i = 0; i < out_ranks.size(); i++)
rank_to_neighbor[out_ranks[i]] = i;
// Count the number of points to send per neighbor process
std::vector<std::int32_t> send_sizes(out_ranks.size());
for (std::size_t i = 0; i < points.size() / 3; ++i)
for (auto p : collisions.links(i))
send_sizes[rank_to_neighbor[p]] += 3;
// Compute receive sizes
std::vector<std::int32_t> recv_sizes(in_ranks.size());
send_sizes.reserve(1);
recv_sizes.reserve(1);
MPI_Request sizes_request;
MPI_Ineighbor_alltoall(send_sizes.data(), 1, MPI_INT, recv_sizes.data(), 1,
MPI_INT, forward_comm, &sizes_request);
// Compute sending offsets
std::vector<std::int32_t> send_offsets(send_sizes.size() + 1, 0);
std::partial_sum(send_sizes.begin(), send_sizes.end(),
std::next(send_offsets.begin(), 1));
// Pack data to send and store unpack map
std::vector<T> send_data(send_offsets.back());
std::vector<std::int32_t> counter(send_sizes.size(), 0);
// unpack map: [index in adj list][pos in x]
std::vector<std::int32_t> unpack_map(send_offsets.back() / 3);
for (std::size_t i = 0; i < points.size(); i += 3)
{
for (auto p : collisions.links(i / 3))
{
int neighbor = rank_to_neighbor[p];
int pos = send_offsets[neighbor] + counter[neighbor];
auto it = std::next(send_data.begin(), pos);
std::copy_n(std::next(points.begin(), i), 3, it);
unpack_map[pos / 3] = i / 3;
counter[neighbor] += 3;
}
}
MPI_Wait(&sizes_request, MPI_STATUS_IGNORE);
std::vector<std::int32_t> recv_offsets(in_ranks.size() + 1, 0);
std::partial_sum(recv_sizes.begin(), recv_sizes.end(),
std::next(recv_offsets.begin(), 1));
std::vector<T> received_points((std::size_t)recv_offsets.back());
MPI_Neighbor_alltoallv(
send_data.data(), send_sizes.data(), send_offsets.data(),
dolfinx::MPI::mpi_type<T>(), received_points.data(), recv_sizes.data(),
recv_offsets.data(), dolfinx::MPI::mpi_type<T>(), forward_comm);
// Get mesh geometry for closest entity
const mesh::Geometry<T>& geometry = mesh.geometry();
std::span<const T> geom_dofs = geometry.x();
auto x_dofmap = geometry.dofmap();
// Compute candidate cells for collisions (and extrapolation)
const graph::AdjacencyList<std::int32_t> candidate_collisions
= compute_collisions(bb, std::span<const T>(received_points.data(),
received_points.size()));
// Each process checks which points collide with a cell on the process
const int rank = dolfinx::MPI::rank(comm);
std::vector<std::int32_t> cell_indicator(received_points.size() / 3);
std::vector<std::int32_t> closest_cells(received_points.size() / 3);
for (std::size_t p = 0; p < received_points.size(); p += 3)
{
std::array<T, 3> point;
std::copy_n(std::next(received_points.begin(), p), 3, point.begin());
// Find first colliding cell among the cells with colliding bounding boxes
const int colliding_cell = geometry::compute_first_colliding_cell(
mesh, candidate_collisions.links(p / 3), point,
10 * std::numeric_limits<T>::epsilon());
// If a collding cell is found, store the rank of the current process
// which will be sent back to the owner of the point
cell_indicator[p / 3] = (colliding_cell >= 0) ? rank : -1;
// Store the cell index for lookup once the owning processes has determined
// the ownership of the point
closest_cells[p / 3] = colliding_cell;
}
// Create neighborhood communicator in the reverse direction: send
// back col to requesting processes
MPI_Comm reverse_comm;
MPI_Dist_graph_create_adjacent(
comm, out_ranks.size(), out_ranks.data(), MPI_UNWEIGHTED, in_ranks.size(),
in_ranks.data(), MPI_UNWEIGHTED, MPI_INFO_NULL, false, &reverse_comm);
// Reuse sizes and offsets from first communication set
// but divide by three
{
auto rescale = [](auto& x)
{ std::ranges::transform(x, x.begin(), [](auto e) { return (e / 3); }); };
rescale(recv_sizes);
rescale(recv_offsets);
rescale(send_sizes);
rescale(send_offsets);
// The communication is reversed, so swap recv to send offsets
std::swap(recv_sizes, send_sizes);
std::swap(recv_offsets, send_offsets);
}
std::vector<std::int32_t> recv_ranks(recv_offsets.back());
MPI_Neighbor_alltoallv(cell_indicator.data(), send_sizes.data(),
send_offsets.data(), MPI_INT32_T, recv_ranks.data(),
recv_sizes.data(), recv_offsets.data(), MPI_INT32_T,
reverse_comm);
std::vector<int> point_owners(points.size() / 3, -1);
for (std::size_t i = 0; i < unpack_map.size(); i++)
{
const std::int32_t pos = unpack_map[i];
// Only insert new owner if no owner has previously been found
if (recv_ranks[i] >= 0 && point_owners[pos] == -1)
point_owners[pos] = recv_ranks[i];
}
// Create extrapolation marker for those points already sent to other
// process
std::vector<std::uint8_t> send_extrapolate(recv_offsets.back());
for (std::int32_t i = 0; i < recv_offsets.back(); i++)
{
const std::int32_t pos = unpack_map[i];
send_extrapolate[i] = point_owners[pos] == -1;
}
// Swap communication direction, to send extrapolation marker to other
// processes
std::swap(send_sizes, recv_sizes);
std::swap(send_offsets, recv_offsets);
std::vector<std::uint8_t> dest_extrapolate(recv_offsets.back());
MPI_Neighbor_alltoallv(send_extrapolate.data(), send_sizes.data(),
send_offsets.data(), MPI_UINT8_T,
dest_extrapolate.data(), recv_sizes.data(),
recv_offsets.data(), MPI_UINT8_T, forward_comm);
std::vector<T> squared_distances(received_points.size() / 3, -1);
for (std::size_t i = 0; i < dest_extrapolate.size(); i++)
{
if (dest_extrapolate[i] == 1)
{
assert(closest_cells[i] == -1);
std::array<T, 3> point;
std::copy_n(std::next(received_points.begin(), 3 * i), 3, point.begin());
// Find shortest distance among cells with colldiing bounding box
T shortest_distance = std::numeric_limits<T>::max();
std::int32_t closest_cell = -1;
for (auto cell : candidate_collisions.links(i))
{
auto dofs = MDSPAN_IMPL_STANDARD_NAMESPACE::submdspan(
x_dofmap, cell, MDSPAN_IMPL_STANDARD_NAMESPACE::full_extent);
std::vector<T> nodes(3 * dofs.size());
for (std::size_t j = 0; j < dofs.size(); ++j)
{
const int pos = 3 * dofs[j];
for (std::size_t k = 0; k < 3; ++k)
nodes[3 * j + k] = geom_dofs[pos + k];
}
const std::array<T, 3> d = compute_distance_gjk<T>(
std::span<const T>(point.data(), point.size()), nodes);
if (T current_distance = d[0] * d[0] + d[1] * d[1] + d[2] * d[2];
current_distance < shortest_distance)
{
shortest_distance = current_distance;
closest_cell = cell;
}
}
closest_cells[i] = closest_cell;
squared_distances[i] = shortest_distance;
}
}
std::swap(recv_sizes, send_sizes);
std::swap(recv_offsets, send_offsets);
// Get distances from closest entity of points that were on the other process
std::vector<T> recv_distances(recv_offsets.back());
MPI_Neighbor_alltoallv(
squared_distances.data(), send_sizes.data(), send_offsets.data(),
dolfinx::MPI::mpi_type<T>(), recv_distances.data(), recv_sizes.data(),
recv_offsets.data(), dolfinx::MPI::mpi_type<T>(), reverse_comm);
// Update point ownership with extrapolation information
std::vector<T> closest_distance(point_owners.size(),
std::numeric_limits<T>::max());
for (std::size_t i = 0; i < out_ranks.size(); i++)
{
for (std::int32_t j = recv_offsets[i]; j < recv_offsets[i + 1]; j++)
{
const std::int32_t pos = unpack_map[j];
auto current_dist = recv_distances[j];
// Update if closer than previous guess and was found
if (auto d = closest_distance[pos];
(current_dist > 0) and (current_dist < d))
{
point_owners[pos] = out_ranks[i];
closest_distance[pos] = current_dist;
}
}
}
// Communication is reversed again to send dest ranks to all processes
std::swap(send_sizes, recv_sizes);
std::swap(send_offsets, recv_offsets);
// Pack ownership data
std::vector<std::int32_t> send_owners(send_offsets.back());
std::ranges::fill(counter, 0);
for (std::size_t i = 0; i < points.size() / 3; ++i)
{
for (auto p : collisions.links(i))
{
int neighbor = rank_to_neighbor[p];
send_owners[send_offsets[neighbor] + counter[neighbor]++]
= point_owners[i];
}
}
// Send ownership info
std::vector<std::int32_t> dest_ranks(recv_offsets.back());
MPI_Neighbor_alltoallv(send_owners.data(), send_sizes.data(),
send_offsets.data(), MPI_INT32_T, dest_ranks.data(),
recv_sizes.data(), recv_offsets.data(), MPI_INT32_T,
forward_comm);
// Unpack dest ranks if point owner is this rank
std::vector<int> owned_recv_ranks;
owned_recv_ranks.reserve(recv_offsets.back());
std::vector<T> owned_recv_points;
std::vector<std::int32_t> owned_recv_cells;
for (std::size_t i = 0; i < in_ranks.size(); i++)
{
for (std::int32_t j = recv_offsets[i]; j < recv_offsets[i + 1]; j++)
{
if (rank == dest_ranks[j])
{
owned_recv_ranks.push_back(in_ranks[i]);
owned_recv_points.insert(
owned_recv_points.end(), std::next(received_points.cbegin(), 3 * j),
std::next(received_points.cbegin(), 3 * (j + 1)));
owned_recv_cells.push_back(closest_cells[j]);
}
}
}
MPI_Comm_free(&forward_comm);
MPI_Comm_free(&reverse_comm);
return PointOwnershipData<T>{.src_owner = std::move(point_owners),
.dest_owners = std::move(owned_recv_ranks),
.dest_points = std::move(owned_recv_points),
.dest_cells = std::move(owned_recv_cells)};
}
} // namespace dolfinx::geometry
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